Prevalence of Cognitive Frailty Phenotypes and Associated Factors in a Community-Dwelling Elderly Population

Ruan, Qingwei; Xiao, Feng; Gong, Ke; Zhang, Wen; Zhang, M.; Ruan, Jian; Zhang, X.; Chen, Q.; Yu, Zhuowei

doi:10.1007/s12603-019-1286-7

Cited by 66 publications

(84 citation statements)

References 47 publications

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“…In addition, our findings indicate that frailty is mostly associated with cognitive impairment, risk of depression, altered nutritional status, and a decline in functional domains (ADL and TUG). This link between frailty and cognitive, nutritional, and functional decline has also been reported in previous studies [21][22][23][24]. Frailty is the most problematic expression of aging.…”

Section: Discussionsupporting

confidence: 81%

Evaluation of pro-inflammatory cytokines in frail Tunisian older adults

et al. 2020

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The present study was undertaken to evaluate serum levels of pro-inflammatory cytokines in Tunisian older adults and to examine the relationships between inflammatory marker levels, geriatric, and biochemical parameters. A cross-sectional study was conducted in a population of Tunisian older adults (N = 141, aged 65 and over). Patients were recruited from the Department of Internal Medicine, Fattouma Bourguiba University Hospital (Monastir, Tunisia) and from a nursing home (Sousse, Tunisia). Comprehensive geriatric assessment, history taking and examination including functional and nutritional assessment were done for each participant. Enzyme-linked immunosorbent assay (ELISA) test was used to measure serum cytokine (TNF-α, IL-8, IL-6) levels. The modified Short Emergency Geriatric Assessment score (SEGAm) were used to classify patients as 51 very-frail, 40 frail, and 50 non-frail. The age of the participants (80 men, 61 women) ranged from 65 to 97 years. Serum levels of TNF-α, IL-8 and C-reactive protein (CRP) were significantly higher in very-frail participants compared to frail and non-frail ones. However, no significant differences in IL-6 levels were detected among frailty groups. After adjustment for age, CRP and IL-8 levels remained significantly associated with frailty. Analysis of the receiver operating characteristic (ROC) curve corresponding to IL-8 showed an area under the curve of 0.7 (p = 0.003; 95% CI [0.58–0.81]) and a predictive threshold of 5.27 pg/ml. Positive correlations were found between frailty score, IL-6, and IL-8 levels. In addition, a significant positive correlation was observed between IL-8 levels and Timed Up and Go test results. However, a negative correlation was observed between Mini Nutritional Assessment Short-Form score, IL-6 and CRP levels, as well as between Activities of Daily Living score and serum levels of TNF-α, IL-6, and CRP. In conclusion, the key findings of this study collectively support a role of pro-inflammatory cytokines, TNF-α, CRP, and especially IL-8 in the development of frailty in older adults.

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Section: Discussionsupporting

confidence: 81%

Evaluation of pro-inflammatory cytokines in frail Tunisian older adults

et al. 2020

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“…A shown in Table 1, numerous criteria were used to diagnose MCI including (1) Petersen's criteria [8,[97][98][99][100][101][102] (n=26 studies [9,); (2) IWG criteria [103] (n=14 studies [45][46][47][48][49][50][51][52][53][54][55][56][57][58]); (3) study specific criteria for CIND (n=10 studies [59][60][61][62][63][64][65][66][67][68]); (4) study specific criteria for MCI (n=13 studies [30, 70, 74-76, 79, 80, 84, 86, 89, 91, 94, 95]); (5) DSM-IV criteria [104] (n=8 studies [72, 77, 78, 81-83, 90, 96]); (6) MCI based on a score from a neuropsychological assessment tool (n=3 studies [69,87,92]); (7) NIA-AA criteria [10] (n=2 studies [11,93]); or, (8) the European Consortium on Alzheimer's Disease (ECAD) criteria [105] (n=2 studies [85,…”

Section: Criteriamentioning

confidence: 99%

Prevalence and Risk of Mild Cognitive Impairment in Low and Middle-Income Countries: A Systematic Review

McGrattan

Zhu

Richardson

et al. 2021

JAD

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Background: Mild cognitive impairment (MCI) is a cognitive state associated with increased risk of dementia. Little research on MCI exists from low-and middle-income countries (LMICs), despite high prevalence of dementia in these settings. Objective: This systematic review aimed to review epidemiological reports to determine the prevalence of MCI and its associated risk factors in LMICs. Methods: Medline, Embase, and PsycINFO were searched from inception until November 2019. Eligible articles reported on MCI in population or community-based studies from LMICs and were included as long as MCI was clearly defined. Results: 5,568 articles were screened, and 78 retained. In total, n = 23 different LMICs were represented; mostly from China (n = 55 studies). Few studies were from countries defined as lower-middle income (n = 14), low income (n = 4), or from population representative samples (n = 4). There was large heterogeneity in how MCI was diagnosed; with Petersen criteria the most commonly applied (n = 26). Prevalence of amnesic MCI (aMCI) (Petersen criteria) ranged from 0.6%to 22.3%. Similar variability existed across studies using the International Working Group Criteria for aMCI (range 4.5%to 18.3%) and all-MCI (range 6.1%to 30.4%). Risk of MCI was associated with demographic (e.g., age), health (e.g., cardio-metabolic disease), and lifestyle (e.g., social isolation, smoking, diet and physical activity) factors. Conclusion: Outside of China, few MCI studies have been conducted in LMIC settings. There is an urgent need for population representative epidemiological studies to determine MCI prevalence in LMICs. MCI diagnostic methodology also needs to be standardized. This will allow for cross-study comparison and future resource planning.

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“…Pre-MCI SCD or MCI usually occur simultaneously with physical frailty, which is termed as reversible cognitive or potentially reversible cognitive frailty [6]. The diagnosis of cognitive frailty subtypes depends mainly on various questionnaires [33, 34] and rapid screening tools [35] that may result in false-positive errors. To integrate our established norm into the diagnosis criteria of cognitive frailty, a clinician can objectively diagnose cognitive frailty subtypes or revalidate these high-risk older people with cognitive frailty in the community assessed by rapid screening tools, and this will be efficient regarding resources and time.…”

Section: Discussionmentioning

confidence: 99%

Demographically Corrected Normative Z Scores on the Neuropsychological Test Battery in Cognitively Normal Older Chinese Adults

Ruan

Xiao²,

Gong

et al. 2020

Dement Geriatr Cogn Disord

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Background: Subjective questionnaires used for the diagnosis of pre-mild cognitive impairment (pre-MCI) and conventional criteria for MCI might mainly result in false-positive diagnostic errors. The integrated criteria based on demographically adjusted total and process Z scores on neuropsychological tests have been validated to be sensitive for measuring pre-MCI, MCI, and MCI subtypes. However, the underrepresentativity of Chinese populations and the complexity in some tests limit the use of the established Z scores in the elderly Chinese population. Objective: The aim of this study was to develop a useful Z score calculator to assess individual cognitive performance after adjustment of the scores on each of the neuropsychological tests according to sex, age, and education and to establish preliminary norms for the objective assessment of cognition function in elderly Chinese individuals. Methods: The neuropsychological test battery consists of measures of performance on different cognitive domains, including episodic memory, language, executive function, processing speed, and attention. Data were obtained from 220 clinically cognitively normal Chinese volunteers aged 60 years or older from the cohort of the Shanghai study of health promotion among frail elderly individuals. Regression models were used to investigate the impact of age, education, and sex on test scores. Z scores were estimated for the different scores by subtracting the predicted mean from the raw score and dividing it by the root mean square error term for any given linear regression model. Results: Preliminary analyses indicated that age, sex, or level of education significantly affected test scores. A series of linear regression models was constructed for all instruments, i.e.: the Trail-Making Test A and B, to assess executive function or attention; the Boston Naming Test and animal list generation, to assess language; delayed free correct responses and the Hopkins Verbal Learning Test-Revised (HVLT-R) recognition, as well as three process scores, i.e., intrusion errors, learning slope, and retroactive interference, from the HVLT-R, to assess memory, by adjusting for the covariates of age, sex, and level of education concurrently. The Z scores on all neuropsychological tests were estimated based on the corresponding regression coefficients. Conclusions: We constructed a multivariable regression-based normative Z score method for the measurement of cognition among older Chinese individuals in the community. The normative score will be useful for the accurate diagnosis of different subtypes of pre-MCI and MCI after preliminary rapid screening in the community.

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Prevalence of Cognitive Frailty Phenotypes and Associated Factors in a Community-Dwelling Elderly Population

Cited by 66 publications

References 47 publications

Evaluation of pro-inflammatory cytokines in frail Tunisian older adults

Evaluation of pro-inflammatory cytokines in frail Tunisian older adults

Prevalence and Risk of Mild Cognitive Impairment in Low and Middle-Income Countries: A Systematic Review

Demographically Corrected Normative <b><i>Z</i></b> Scores on the Neuropsychological Test Battery in Cognitively Normal Older Chinese Adults

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